Evidence map›Paper›PMID 26000634›Full record

ArticlePloS one2015

The Patient- And Nutrition-Derived Outcome Risk Assessment Score (PANDORA): Development of a Simple Predictive Risk Score for 30-Day In-Hospital Mortality Based on Demographics, Clinical Observation, and Nutrition.

Michael Hiesmayr, Sophie Frantal, Karin Schindler, Michael Themessl-Huber, Mohamed Mouhieddine, Christian Schuh, Elisabeth Pernicka, Stéphane Schneider, Pierre Singer, Olle Ljunqvist and 4 more

Erratum issued Registry-linked trialAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. It is linked to trial NCT02820246 (NutritionDay in Worldwide Hospitals), which is not on this map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT02820246 unknown statusnot on this map

NutritionDay in Worldwide Hospitals: A Cross-sectional Registry

Typeobservational_patient_registrySponsorMedical University of ViennaRan2006 to 2025Enrolled250,000ConditionsMalnutritionArmsnutrition
3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Michael HiesmayrDepartment of Anaesthesiology, General Intensive Care and Pain Control, Division Cardiac-, Thoracic-, Vascular Anaesthesia and Intensive Care, Medical University Vienna, Vienna, Austria.
Sophie FrantalCenter for Medical Statistics, Informatics and Intelligent Systems, Section for Medical Statistics, Vienna, Austria.
Karin SchindlerMedical Clinic III, Division Endocrinology, Medical University Vienna, Vienna, Austria.
Michael Themessl-HuberCenter for Medical Statistics, Informatics and Intelligent Systems, Section for Medical Statistics, Vienna, Austria.
Mohamed MouhieddineDepartment of Anaesthesiology, General Intensive Care and Pain Control, Division Cardiac-, Thoracic-, Vascular Anaesthesia and Intensive Care, Medical University Vienna, Vienna, Austria.
Christian SchuhCenter for Medical Statistics, Informatics and Intelligent Systems, Section for Medical Statistics, Vienna, Austria.
Elisabeth PernickaCenter for Medical Statistics, Informatics and Intelligent Systems, Section for Medical Statistics, Vienna, Austria.
Stéphane SchneiderNutritional Support Unit, Pôle Digestif, Hôpital de l'Archet, Nice, France.
Pierre SingerGeneral Intensive Care Department, Rabin Medical Center University Hospital, Beilinson Campus, Petah Tiqwa, Israel.
Olle LjunqvistDepartment of Surgery, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
Claude PichardClinical Nutrition, Geneva University Hospital, Geneva, Switzerland.
Alessandro LavianoDepartment of Clinical Medicine, University La Sapienza, Rome, Italy.
Sigrid KosakDepartment of Anaesthesiology, General Intensive Care and Pain Control, Division Cardiac-, Thoracic-, Vascular Anaesthesia and Intensive Care, Medical University Vienna, Vienna, Austria.
Peter BauerCenter for Medical Statistics, Informatics and Intelligent Systems, Section for Medical Statistics, Vienna, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo develop a simple scoring system to predict 30 day in-hospital mortality of in-patients excluding those from intensive care units based on easily obtainable demographic, disease and nutrition related patient data.

methodsScore development with general estimation equation methodology and model selection by P-value thresholding based on a cross-sectional sample of 52 risk indicators with 123 item classes collected with questionnaires and stored in an multilingual online database.

settingWorldwide prospective cross-sectional cohort with 30 day in-hospital mortality from the nutritionDay 2006-2009 and an external validation sample from 2012.

resultsWe included 43894 patients from 2480 units in 32 countries. 1631(3.72%) patients died within 30 days in hospital. The Patient- And Nutrition-Derived Outcome Risk Assessment (PANDORA) score predicts 30-day hospital mortality based on 7 indicators with 31 item classes on a scale from 0 to 75 points. The indicators are age (0 to 17 points), nutrient intake on nutritionDay (0 to 12 points), mobility (0 to 11 points), fluid status (0 to 10 points), BMI (0 to 9 points), cancer (9 points) and main patient group (0 to 7 points). An appropriate model fit has been achieved. The area under the receiver operating characteristic curve for mortality prediction was 0.82 in the development sample and 0.79 in the external validation sample.

conclusionsThe PANDORA score is a simple, robust scoring system for a general population of hospitalised patients to be used for risk stratification and benchmarking.

Indexed as

Hospital MortalityAge FactorsHumansPatient Outcome AssessmentPredictive Value of TestsProspective StudiesRiskRisk AssessmentSeverity of Illness Index

Identifiers

PMID26000634
PMCPMC4441510

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.